# Simple ReAct Agent for System Administration

This directory contains a simple ReAct (Reasoning and Acting) agent implementation for system administration, log analysis, and remote server management tasks.

## Overview

The simple ReAct agent follows a straightforward pattern:
1. **Receives** user input
2. **Reasons** about what tools to use
3. **Acts** by executing tools when needed (locally or remotely)
4. **Responds** with the final result

## Features

- **Single Agent**: One agent handles all tasks
- **Local Shell Access**: Execute system commands on the local machine
- **Remote SSH Access**: Execute commands on remote servers via persistent SSH connections
- **System Administration**: Comprehensive system diagnostics and management
- **Log Analysis**: Specialized log analysis capabilities
- **Interactive Chat**: Stream responses with tool usage visibility
- **Conversation History**: Maintains context across interactions

## Architecture

```
User Input → ReAct Agent → Tools (Shell + SSH + Tools) → Response
```

## Files

- `main.py`: Main application with ReAct agent implementation
- `custom_tools/`: Directory containing custom tools (poem generation tool)

## Tools Available

1. **Shell Tool**: Execute system commands on the local machine
   - System monitoring (`top`, `ps`, `df`, etc.)
   - File operations
   - Network diagnostics

2. **SSH Tool**: Execute commands on remote servers
   - Persistent SSH connections
   - Remote system administration
   - Cross-platform remote diagnostics
   - Secure remote command execution

3. **Poem Tool**: Generate beautiful poems with different themes:
   - `nature`: Poems about nature and the environment
   - `tech`: Poems about technology and programming
   - `motivational`: Inspirational and motivational poems
   - `friendship`: Poems about friendship and relationships
   - `random`: Randomly selects from any available poem type

## Usage

```bash
cd simple-react-agent
python main.py
```

### Example Interactions

```
User: Analyze the Apache logs for error patterns
Agent: 🔧 Using tool: analyze_log_file
       Args: {'file_path': 'Apache/Apache_2k.log', 'analysis_type': 'error_patterns'}
       📋 Tool result: Found 15 error patterns in Apache logs...

User: Check disk usage on the system
Agent: 🔧 Using tool: shell
       Args: {'command': 'df -h'}
       📋 Tool result: Filesystem usage information...

User: Connect to my remote server and check CPU usage
Agent: 🔧 Using tool: configured_ssh_tool
       Args: {'command': 'top -bn1 | head -20'}
       📋 Tool result: Remote server CPU and process information...
```

## Pros and Cons

### ✅ Pros
- **Simple to understand**: Single agent, clear flow
- **Easy to debug**: Linear execution path
- **Quick setup**: Minimal configuration required
- **Resource efficient**: Lower computational overhead
- **Good for**: Simple tasks, learning, rapid prototyping

### ❌ Cons
- **Limited specialization**: One agent handles everything
- **No parallel processing**: Sequential tool execution
- **Scaling challenges**: Complex tasks may overwhelm single agent
- **Less sophisticated**: No coordination between specialized experts

## When to Use

Choose the simple ReAct agent when:
- You need a straightforward system administration tool
- You want both local and remote server management capabilities
- Your use cases are relatively simple
- You want to understand LangGraph basics
- Resource usage is a concern
- You prefer simplicity over sophisticated multi-agent coordination

## Requirements

```bash
pip install langchain-openai langgraph langchain-community
export OPENAI_API_KEY="your-api-key"
```